Space: Apache Mahout (https://cwiki.apache.org/confluence/display/MAHOUT) Page: ClassifyingYourData (https://cwiki.apache.org/confluence/display/MAHOUT/ClassifyingYourData)
Change Comment: --------------------------------------------------------------------- Not 0.2 specific, though I had trouble finding the Breiman Example page after finding this page in Google Edited by Tai: --------------------------------------------------------------------- +*Mahout_0.2*+ After you've done the [Quickstart] and are familiar with the basics of Mahout, it is time to build a classifier from your own data. The following pieces *may* be useful for in getting started: h1. Input For starters, you will need your data in an appropriate Vector format (which has changed since Mahout 0.1) * See [Creating Vectors] h2. Text Preparation * See [Creating Vectors from Text] * http://www.lucidimagination.com/search/document/4a0e528982b2dac3/document_clustering h1. Running the Process h2. Naive Bayes Background: [Naive Bayes Classification | bayesian ] Documentation of running naive bayes from the command line: [bayesian-commandline] h2. C-Bayes Background: [C-Bayes Classification | https://issues.apache.org/jira/browse/MAHOUT-60 ] Documentation of running c-bayes from the command line: [c-bayes-commandline] h2. Random Forests Background: [Random Forests Classification | http://cwiki.apache.org/MAHOUT/random-forests.html ] Documentation of running random forests from the command line: [Breiman Example] Change your notification preferences: https://cwiki.apache.org/confluence/users/viewnotifications.action
